Acoustic radiation forced impulse-based splenic prediction model using data mining for the noninvasive prediction of esophageal varices in hepatitis C virus advanced fibrosis

Abstract

Background Esophageal varices (EV) are serious complications of hepatitis C virus (HCV) cirrhosis. Endoscopic screening is expensive, invasive, and uncomfortable. Accordingly, noninvasive methods are mandatory to avoid unnecessary endoscopy. Acoustic radiation forced impulse (ARFI) imaging using point shear wave elastography as demonstrated with virtual touch quantification is a possible noninvasive EV predictor. We aimed to validate the reliability of liver stiffness (LS) and spleen stiffness (SS) by an ARFI-based study together with other noninvasive parameters for EV prediction in HCV patients. Also, we aimed to evaluate the diagnostic performance of a new simple prediction model (incorporating SS) using data mining analysis. Patients and methods This cross-sectional study included 200 HCV patients with advanced fibrosis. Labs, endoscopic, ultrasonographic, LS, and SS data were collected. Their accuracy in diagnosing EV was assessed and a data mining analysis was carried out. Results Ninety patients (22/46% of F3/F4 patients) had EV (39/30/18/3 patients had grade I/II/III/IV, respectively). LS and SS by ARFI showed high significance in differentiating not only patients with/without EV (P = 0.000 for both) but also correlated with the grading of varices (R = 0.31 and 0.45, respectively; P = 0.000 for both). Spleen longitudinal diameter (SD), splenic vein diameter (SVD), platelets to spleen diameter ratio, LOK index, and FIB-4 score were the best ultrasonographic and biochemical predictors for the prediction of EV [area under receiver operating characteristic (AUROC) 0.79, 0.76, 0.76, 0.74, and 0.71, respectively]. SS (using ARFI) had better diagnostic performance than LS for the prediction of EV (AUROC = 0.76 and 0.70, respectively). The diagnostic performance increased using data mining to construct a simple prediction model: high probability for EV if [(SD cm) × 0.17 + (SVD mm) × 0.06 + (SS) × 0.97] more than 6.35 with AUROC 0.85. Conclusion SS by ARFI represents a reliable noninvasive tool for the prediction of EV in HCV patients, especially when incorporated into a new data mining-based prediction model.

Non‐invasive assessment of fibrosis regression and portal hypertension in patients with advanced chronic hepatitis C virus (HCV)‐associated liver disease and sustained virologic response (SVR): 3 years follow‐up of a prospective longitudinal study

“…A number of studies have investigated spleen stiffness as a non‐invasive parameter for portal hypertension 24–26 . In a recent trial, elevated spleen stiffness measured by ARFI (S‐ARFI) represented a reliable non‐invasive tool for the prediction of oesophageal varices in HCV‐infected patients 27 …”

Small varices in chronic liver diseases

“…Fierbinteanu- Braticevici C et al showed the AUROC for the detection of EVs using SS was 0.776 [53]. SS is suggested to be superior to LS in detecting EVs [54,55,56 ▪ ]. However, in studies of Munoz-Codoceo C and others, LS and SS are suboptimal or only have modest accuracy for detecting varices [57 ▪ ,58,59].…”

The values of elastic quantitative and semi-quantitative indexes measured from different frequencies in the establishment of prediction models for breast tumor diagnosis

“…Therefore, exploring the best frequency of breast elastic ultrasound is highly important for improving its diagnostic value. Previous research results showed that objective and quantitative imaging indexes could effectively reflect the prognosis or prediction of the disease [6][7][8]. Moreover, the diagnosis based on a combination of multiple indexes is more promising than the diagnosis based on a single index, and it is good enough to affect clinical decisions.…”